1. Field
The present disclosure relates generally to the fields of metabolic flux determination, microscopy and functional histopathology, and more specifically to in situ spatial imaging, mapping and display of dynamic metabolic processes in histopathology specimens.
2. Related Art
Breast cancer development involves dynamic and reciprocal interactions between neoplastic cells, activated stromal cells, extracellular matrix (ECM) and soluble molecules in their vicinity. Together these environmental factors foster the malignant phenotype. Intertwined with these hallmarks of cancer development is the fact that tumor cells metabolize glucose largely via aerobic glycolysis as opposed to oxidative phosphorylation, and produce lactate in a less energy-efficient manner, i.e., the Warburg effect [1]. This distinct metabolic state is common to most solid tumors, including breast cancers, and is thought to contribute to their chemo-resistance. Thus altered metabolism may limit efficacy of standard anti-cancer therapy, but this feature may also be used to identify and characterize subtypes of neoplastic tissue.
Altered metabolic flux is critical to the malignant phenotype. The dependence on aerobic glycolysis and intimate linkage between Raf/MEK/ERK, PI3K/Akt pathway[2, 3], and microenvironment suggest strong causal relationships between these signaling networks, drug resistance, metabolite transport, microenvironment, and metabolism. Hence, altered metabolism can provide a mechanism to support a proliferative phenotype through aerobic glycolysis, drive evolution, and drug resistance through dormancy and altered lipid metabolism. For example, it has recently been suggested that aerobic glycolysis provides metabolic precursors necessary for rapid growth (i.e. membrane biosynthesis)[4].
Significant progress has been made in applying molecular profiling to characterize cancer phenotype. Transcriptomic profiles have been identified that predict prognosis or response to treatment for cancers[5] including alterations in cancer metabolism[6]. In fact cancer cells exhibit a wide variety of abnormalities in metabolic fluxes [7], including numerous alterations in the synthesis and turnover of lipids[8] which are required to support the malignant phenotype through structural roles in membranes (e.g., cholesterol, phospholipids), signaling pathways (e.g., prostanoids, glycolipids) and mediation of pathways and organelle function (e.g. ER transport, mitochondrial biogenesis). However, tumors are often comprised of heterogeneous cell populations and therefore lipid turnover must be studied using imaging approaches to capture critical information on cellular sub-populations and microenvironmental effects.
Pathological techniques have always been critical in the diagnosis and treatment of cancer. Classic morphologic criteria, based on vital dyes and light microscopy, have been complemented by immunohistochemistry and gene expression profiling, leading to histological markers of growth factor receptor status or transcriptomic signatures, that, for example, predict an individual's likely treatment response[12]. However, all current histological analyses are ‘blind’ to the spatially ordered metabolic dynamics of the tumor. Metabolic fluxes are closer to function than static markers and may therefore correlate better with phenotypic behavior.
Metabolomic measurement provides direct information on downstream biochemical processes making this type of measurement an excellent complement to other systems or approaches focused on alterations in genetics and gene expression[13]. The two major technologies are Nuclear Magnetic Resonance (NMR or MR) and mass spectrometry (MS). These two approaches are complementary. NMR has the advantage that it allows real time non-invasive imaging using tracers and more recently using hyperpolarized molecules[14]. The sensitivity and dynamic range of mass spectrometry are many orders higher [15], making mass spectrometry a method of choice for untargeted studies that can feed into the development of NMR imaging studies. MS approaches coupled to chromatography maximize the number of metabolites detected and can quantify and identify (from MS/MS fragmentation patterns) with very high sensitivity from extremely complex mixtures[16]. However, the requisite sample homogenization and preparation results in a loss of spatial information, with averaging of metabolite concentrations, and loss of information of critical tumor subpopulations. Mass spectrometry based imaging has emerged to address this limitation[16] and the proposed work lays the groundwork for application all of the various technologies. Major approaches include: Time-of-Flight Secondary Ionization Mass Spectrometry (TOF-SIMS) [17, 18], which has the highest spatial resolution (˜100 nm), but the extensive fragmentation which often complicates molecular characterization and the lack of tandem MS capabilities on commercial instruments limits identification. Matrix Assisted Laser Desorption Ionization (MALDI) [19] is a method of choice for intact protein imaging however metabolite imaging is complicated by matrix interference in the low mass range (<500 Da). The spatial resolution of MALDI corresponds to the matrix crystal size (typically ˜50-75 um), but this can be reduced using special matrix deposition imaging approaches[20]. Recently, a new soft ionization and atmospheric pressure technique termed Desorption Electrospray Ionization (DESI) [21, 22] has emerged as an alternative approach to MALDI and SIMS. Unfortunately, tissue imaging by DESI shows relatively low spatial resolution (˜100 um) and is currently incapable of imaging tissues at the cellular level.